The automatic analysis of human handwriting begins with sampling and digitization of the image or signal produced directly by human manipulation of a writing instrument, referred to herein, in a general sense, as a stylus. Purely graphical analysis can be performed on data sampled from a static image. However, for dynamic analysis, and more generally for analyzing data with reference to a temporal sequence, it is advantageous for the human subject to produce data by manipulating an instrumented stylus or tablet that permits spatiotemporal sampling.
One exemplary instrumented tablet is described in U.S. Pat. No. 5,463,388, issued on Oct. 31, 1995 to R. A. Boie et al. This tablet includes a rectangular array of capacitance-sensing electrodes. The position of a handheld stylus is determined, e.g., from the centroid of the respective capacitance values, as calculated in a microcontroller.
Parametric methods have been used for a number of years in connection, for example, with automatic signature verification. According to these methods, the signature (or other handwritten symbol) is represented in an abstract parameter space. The parametric representation consists of a set of numerical values of functions that are evaluated on the sampled data, and that relate to some combination of graphical and dynamic properties of the sampled data. Generally, a parametric representation is a condensed representation, in the sense that it occupies fewer bits of data-storage capacity than do the raw, sampled data.
Parametric representations of signatures have been used with some success for signature verification. In signature verification, the parameters are evaluated on a newly entered signature (or group of signatures), and the results are compared with a stored set of reference values. Such a procedure does not require the reconstruction, from parameters, of either the reference signature or the newly entered signature. Therefore, there is no need to choose parameters that preserve enough graphical information to reconstruct these signatures. Instead, parameters for signature verification are selected on the basis, e.g., of a tradeoff between selectivity and computational efficiency.
However, there is a need for a compact method for storing handwritten symbols that can later be reconstructed as legible characters. For such a purpose, it is not sufficient to use the abstract parameters that are often used in the context of signature verification. On the other hand, the more detailed the shape information that is used, the less compact the resulting storage method will be.
What the field has lacked, until now, are methods for storing and reconstructing characters that enjoy the benefits of compact parametric techniques, but still lead to clearly legible reconstructed characters.